{"_id":"10736","month":"01","day":"26","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","quality_controlled":"1","file_date_updated":"2022-02-07T07:14:09Z","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"article_number":"e64543","file":[{"relation":"main_file","file_id":"10739","date_created":"2022-02-07T07:14:09Z","checksum":"decdcdf600ff51e9a9703b49ca114170","success":1,"date_updated":"2022-02-07T07:14:09Z","access_level":"open_access","file_size":5604343,"file_name":"2022_ELife_Lagator.pdf","content_type":"application/pdf","creator":"cchlebak"}],"ec_funded":1,"language":[{"iso":"eng"}],"isi":1,"publication_status":"published","date_updated":"2023-08-02T14:09:02Z","has_accepted_license":"1","date_created":"2022-02-06T23:01:32Z","abstract":[{"lang":"eng","text":"Predicting function from sequence is a central problem of biology. Currently, this is possible only locally in a narrow mutational neighborhood around a wildtype sequence rather than globally from any sequence. Using random mutant libraries, we developed a biophysical model that accounts for multiple features of σ70 binding bacterial promoters to predict constitutive gene expression levels from any sequence. We experimentally and theoretically estimated that 10–20% of random sequences lead to expression and ~80% of non-expressing sequences are one mutation away from a functional promoter. The potential for generating expression from random sequences is so pervasive that selection acts against σ70-RNA polymerase binding sites even within inter-genic, promoter-containing regions. This pervasiveness of σ70-binding sites implies that emergence of promoters is not the limiting step in gene regulatory evolution. Ultimately, the inclusion of novel features of promoter function into a mechanistic model enabled not only more accurate predictions of gene expression levels, but also identified that promoters evolve more rapidly than previously thought."}],"oa":1,"publication_identifier":{"eissn":["2050-084X"]},"publisher":"eLife Sciences Publications","intvolume":" 11","pmid":1,"author":[{"full_name":"Lagator, Mato","last_name":"Lagator","first_name":"Mato","id":"345D25EC-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Srdjan","id":"35F0286E-F248-11E8-B48F-1D18A9856A87","full_name":"Sarikas, Srdjan","last_name":"Sarikas"},{"last_name":"Steinrueck","full_name":"Steinrueck, Magdalena","first_name":"Magdalena"},{"full_name":"Toledo-Aparicio, David","last_name":"Toledo-Aparicio","first_name":"David"},{"first_name":"Jonathan P","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4624-4612","full_name":"Bollback, Jonathan P","last_name":"Bollback"},{"first_name":"Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","full_name":"Guet, Calin C","last_name":"Guet"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","last_name":"Tkačik","full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455"}],"article_processing_charge":"No","external_id":{"pmid":["35080492"],"isi":["000751104400001"]},"department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"NiBa"}],"title":"Predicting bacterial promoter function and evolution from random sequences","doi":"10.7554/eLife.64543","article_type":"original","project":[{"_id":"2578D616-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"648440","name":"Selective Barriers to Horizontal Gene Transfer"}],"oa_version":"Published Version","scopus_import":"1","status":"public","acknowledgement":"We thank Hande Acar, Nicholas H Barton, Rok Grah, Tiago Paixao, Maros Pleska, Anna Staron, and Murat Tugrul for insightful comments and input on the manuscript. This work was supported by: Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant number 216779/Z/19/Z) to ML; IPC Grant from IST Austria to ML and SS; European Research Council Funding Programme 7 (2007–2013, grant agreement number 648440) to JPB.","ddc":["576"],"year":"2022","type":"journal_article","publication":"eLife","date_published":"2022-01-26T00:00:00Z","citation":{"apa":"Lagator, M., Sarikas, S., Steinrueck, M., Toledo-Aparicio, D., Bollback, J. P., Guet, C. C., & Tkačik, G. (2022). Predicting bacterial promoter function and evolution from random sequences. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.64543","mla":"Lagator, Mato, et al. “Predicting Bacterial Promoter Function and Evolution from Random Sequences.” ELife, vol. 11, e64543, eLife Sciences Publications, 2022, doi:10.7554/eLife.64543.","short":"M. Lagator, S. Sarikas, M. Steinrueck, D. Toledo-Aparicio, J.P. Bollback, C.C. Guet, G. Tkačik, ELife 11 (2022).","chicago":"Lagator, Mato, Srdjan Sarikas, Magdalena Steinrueck, David Toledo-Aparicio, Jonathan P Bollback, Calin C Guet, and Gašper Tkačik. “Predicting Bacterial Promoter Function and Evolution from Random Sequences.” ELife. eLife Sciences Publications, 2022. https://doi.org/10.7554/eLife.64543.","ieee":"M. Lagator et al., “Predicting bacterial promoter function and evolution from random sequences,” eLife, vol. 11. eLife Sciences Publications, 2022.","ista":"Lagator M, Sarikas S, Steinrueck M, Toledo-Aparicio D, Bollback JP, Guet CC, Tkačik G. 2022. Predicting bacterial promoter function and evolution from random sequences. eLife. 11, e64543.","ama":"Lagator M, Sarikas S, Steinrueck M, et al. Predicting bacterial promoter function and evolution from random sequences. eLife. 2022;11. doi:10.7554/eLife.64543"},"volume":11}